Biomarker for the prediction of responsiveness to an anti-tumour necrosis factor alpha (tnf) treatment

ABSTRACT

The invention refers to a method for diagnosing an individual who is to be subjected to or is being subjected to an anti-tumour necrosis factor alpha (TNFα or TNF) treatment to assess the responsiveness to an anti-TNF treatment which comprises the detection of immunoglobulin(s) against one or more biomarker proteins in a bodily fluid or an excrement of said patient, and sorting the individual into one of two categories based on detection of said immunoglobulin(s), wherein individuals are classified as NON-responder or responder. The invention refers to diagnostic kits comprising said one or more biomarker proteins and the use of these kits for assessing the responsiveness to an anti-TNF treatment of an individual who is to be subjected to or is being subjected to an anti-TNFα treatment.

The invention refers to a method for diagnosing an individual who is to be subjected to or is being subjected to an anti-tumour necrosis factor alpha (TNFα or TNF) treatment to assess the responsiveness to an anti-TNF treatment which comprises the detection of immunoglobulin(s) against one or more biomarker proteins in a bodily fluid or an excrement of said patient, and sorting the individual into one of two categories based on detection of said immunoglobulin(s), wherein individuals are classified as NON-responder or responder. The invention refers to diagnostic kits comprising said one or more biomarker proteins and the use of these kits for assessing the responsiveness to an anti-TNF treatment of an individual who is to be subjected to or is being subjected to an anti-TNFα treatment.

BACKGROUND

Rheumatic diseases are the most common chronic inflammatory disorders. In Germany alone, one million patients suffer from immunologically mediated rheumatic diseases including rheumatoid arthritis (RA), spondyloarthropathies (SpA) and systemic autoimmune diseases like systemic lupus erythematosus (SLE), while additional five million individuals have osteoarthritis (OA), a primarily degenerative joint disease, which, however, in its active phases is also dominated by inflammatory processes. Rheumatoid arthritis leads to severe pain, loss of function and serious impairment of the quality of life. Besides these deleterious consequences for the individual patient, there is a striking socio-economic impact leading to direct and indirect costs of about 20 billion Euros in Germany per year. The demographic development clearly indicates that rheumatic diseases will dramatically increase over the next decades and will be equal in importance to cardiovascular diseases and cancer. Already now, rheumatic disorders dominate the number of patient visits in the General Practitioner's office and are the leading cause of absence from work and premature invalidity. In recognition of the tremendous impact of arthritic and bone diseases, the World Health Organization has announced the current decade as the “Decade of Bone and Joint Diseases”.

A range of therapies for rheumatoid arthritis is available based on standard disease-modifying antirheumatic drugs (DMARDs), such as Methotrexate (MTX) and on biologicals, such as TNF inhibitors/antagonists. Chronically elevated levels of TNF have been implicated as a pathogenic component in rheumatoid arthritis. TNF inhibitors are biologicals which bind to soluble and cell membrane-associated form of TNFα and neutralise the proinflammatory effect of TNFα by preventing the binding of TNFα to the TNF-RI/II cell-surface receptors. TNFa-inhibiting biological agents comprise e.g. therapeutic antibodies (Adalimumab® & Infliximab®) and soluble receptor constructs (Etanercept®). These biologicals are currently used to treat active rheumatoid arthritis, all of which effectively reduce the signs and symptoms of the disease and inhibit radiographic joint damage progression. Currently ˜10% of patients in Germany, but up to 30% in Scandinavian countries are treated with TNF-α inhibitors and the numbers are continuously growing. Anti-TNF-α antibodies (Adalimumab®; Humira) account for 90% of all biologicals in current use of rheumatoid arthritis therapy.

However, only 70% of rheumatoid arthritis patients benefit from a treatment with anti-TNFα, while 30% (˜10.000 patients in Germany in 2006) remain non-responders. An anti-TNFα therapy costs currently ˜20.000

in Germany and hence, the costs of unsuccessful therapies account for 200 Mia

/year in Germany alone.

Next to rheumatoid arthritis, chronically elevated levels of TNF have been implicated as a pathogenic component in a number of other disease states—primarily autoimmune conditions—such as psoriasis, psoriatic arthritis, ankylosing spondylitis, Crohn's disease, ulcerative colitis, etc.

Currently, there are no biomarkers available, which can predict the outcome of a treatment with anti-TNF agents (e.g. TNF antagonists/inhibitors) prior treatment. Only reduction of all isotype levels of rheumatoid factors during and after treatment is associated with a positive response and outcome of the treatment (van Laar J M. Nat Clin Pract Rheumatol. 2007 October; 3(10):544-5. PMID: 17726429). However, high level of IgA rheumatoid factor in sera of patients with rheumatoid arthritis has been suggested to identify a subgroup of patients at risk of a poor clinical response to treatment with anti-TNFα antibodies (Bobbio-Pallavicini F. et al. Ann Rheum Dis. 2007 March; 66(3):302-7. PMID: 17079248; Bobbio-Pallavicini F. et al. Ann NY Acad Sci. 2007 August; 1109:287-95. PMID: 17785317; van Laar J M. Nat Clin Pract Rheumatol. 2007 October; 3(10):544-5. PMID: 17726429). The nature of anti-CCP antibodies suggested as a predictor for therapy efficacy is controversial (Braun-Moscovici Y et al. J Rheumatol. 2006 March; 33(3):497-500. PMID: 16511906; Bobbio-Pallavicini F et al. Ann NY Acad Sci. 2007 August; 1109:287-95. PMID: 17785317; van Laar J M. Nat Clin Pract Rheumatol. 2007 October; 3(10):544-5. PMID: 17726429).

Thus, there is a need in the art for markers, which can predict the outcome of an anti-TNFα therapy prior to and during treatment. There is a need for stratification of patients who are to be subjected to or are being subjected to an anti-TNFα treatment and distinguishing between anti-TNFα treatment responder and Non-responder patients.

Subject of the present invention is a method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment to assess the responsiveness to an anti-TNF treatment prior, during and/or after anti-TNFα treatment which comprises:

-   -   a. Detection of immunoglobulin(s) against one or more biomarker         proteins in a bodily fluid or excrement of said patient, wherein         the one or more biomarker is indicative for the responsiveness         to an anti-TNF treatment prior, during and after anti-TNFα         treatment.     -   b. Sorting the individual into responder or NON-responder based         on detection of said immunoglobulin(s).

Thus, the invention provides for the first time marker which can predict the outcome of an anti-TNFα treatment prior to treatment in addition to during and/or after treatment. Anti-TNFalpha treatment may be conducted by administration of TNF inhibitors, e.g. TNF antagonists. These markers are not related to IgA rheumatoid factor. The marker according to the present invention can either be indicative of responder or of NON-responder as will be outlined below in detail. It is preferred that the responsiveness is assessed prior to treatment.

Subject of the present invention is a method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment to assess the responsiveness to an anti-TNF treatment which comprises:

-   -   Detection of immunoglobulin(s) against one or more biomarker         proteins in a bodily fluid or an excrement of said patient,         wherein a biomarker protein is an expression product encoded by         a gene selected from the group comprising RAB11B, PPP2R1A,         KPNB1, COG4 and FDFT1, wherein an individual positive for at         least one of said immunoglobulin(s) is classified as         NON-responder.

In a preferred embodiment of the above-identified method the individual is sorted into one of two categories based on detection of said immunoglobulin(s), wherein an individual positive for at least one of said immunoglobulin(s) is classified as NON-responder and, wherein an individual negative for any of said detected immunoglobulin(s) is classified as responder.

In a preferred embodiment of the inventive method at least two of the biomarker proteins of the protein marker group are detected wherein a biomarker protein is an expression product encoded by a gene selected from the group comprising RAB11B, PPP2R1A, KPNB1, COG4 and FDFT1 (Protein Set 1=RAB11B, PPP2R1A, KPNB1, COG4 and FDFT1). In another preferred embodiment of the inventive method at least expression products encoded by genes RAB11B, PPP2R1A, KPNB1, COG4 and FDFT1 are detected. In another preferred embodiment only expression products encoded by genes RAB11B, PPP2R1A, KPNB1, COG4 and FDFT1 are detected. In another preferred embodiment each and only the expression products encoded by genes RAB11B, PPP2R1A, KPNB1, COG4 and FDFT1 are detected.

In another preferred embodiment of the method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment according to the invention the biomarker protein group additionally comprises at least one other expression product encoded by a gene selected from the group comprising PECI, CTNND2, NSMCE1, KTELC1, HS6ST1, ARMC6, TH1L, PSME1, GPC1, EDC4 (Protein Set 2) and at least one of the proteins of the entire group 1 and 2 (Protein Set 1 and 2) is detected. In a preferred embodiment of the invention at least one protein from Protein Set 1 is detected and additionally at least one of Protein Set 2 is detected. In another preferred embodiment at least two of the proteins of Protein Set 1 and additionally at least one of Protein Set 2 are detected. In another preferred embodiment Protein Set 1 and Protein Set 2 are detected.

In another preferred embodiment additionally to the above cited combinations of marker proteins a protein of Protein Set 3 is detected: the Protein Set 3 comprises the expression products encoded by genes PRC1, NAT6, EEF1AL3, NP_(—)612480.1, PLXNA2, ELMO2 and NDUFS2.

In another preferred embodiment of the invention at least two marker proteins are selected from the group comprising the marker from protein sets 1, 2 and 3 for the method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment to assess the responsiveness to an anti-TNF treatment prior, during and/or after anti-TNFα treatment. This means in this embodiment at least two marker are selected from the group comprising RAB11B, PPP2R1A, KPNB1, COG4, FDFT1, PECI, CTNND2, NSMCE1, KTELC1, HS6ST1, ARMC6, TH1L, PSME1, GPC1, EDC4, PRC1, NAT6, EEF1AL3, NP_(—)612480.1, PLXNA2, ELMO2 and NDUFS2.

In another preferred embodiment at least three marker proteins are selected, more preferably four or five protein marker.

According to the present invention biomarker proteins of the present invention may be peptides, protein fragments, full length or splice variants or synthetically modified derivatives or post-translationally modified versions of the proteins encoded by aforementioned genes. Preferably, said protein fragments have a length of more than nine amino acids, more preferably at least n twelve or more than twelve amino acids. Modification of proteins may be but are not limited to deimination, deamidation and/or transglutamination. Additionally, they can be artificial polypeptides being expression products derived from incorrect reading frames within the gene. An examples for such an expression product derived from incorrect reading frames within the gene is shown in FIG. 122 which is a protein sequence derived from an incorrect reading frame of the gene HS6SP1. Another example is shown in FIG. 121 which is a protein sequence derived from an incorrect reading frame of the gene C20orfl149. Yet another example is shown in FIG. 120 which is a protein sequence derived from an incorrect reading frame of the gene IRAK1.

This means when for example IRAK1 is mentioned in the context of the present application it may concern the peptides, protein fragments, full length or splice variants or synthetically modified derivatives and/or post-translationally modified versions of IRAK1 and/or a protein sequence derived from an incorrect reading frame of the gene IRAK1.

A biomarker protein encompasses also variants thereof, such as peptides, protein fragments, artificial polypeptides, full length or splice variants, synthetically modified derivatives or post-translationally modified versions of the proteins encoded by aforementioned genes which are characterized in that these variants exhibit essentially the same ability to be recognized by the respective immunoglobulin as the biomarker proteins that are subject of the invention.

In particular, according to the present inventions biomarker proteins are encompassed wherein the sequences involved in binding to the respective immunoglobulin exhibit at least 80%, preferred at least 90%, more preferred at least 95% degree of sequence identity on the amino acid level to the sequences involved in binding of the biomarker proteins defined in SEQ ID No.s 59-122 as well as peptides, protein fragments, full length or splice variants, synthetically modified derivatives or post-translationally modified versions thereof exhibiting the same ability.

In context of the present invention a DNA sequence of a gene is defined by comprising all exons of a gene necessary to represent the protein coding sequence (CDS) or all splice variants thereof, as well as the exons representing the 5′ untranslated region (UTR) and the 3′ UTR.

According to the present invention all DNA sequences are encompassed which encode the before-mentioned biomarker proteins.

In particular, according to the present inventions furthermore DNA sequences are encompassed which exhibit referred to the sequence encoding a stretch which is involved in the binding region at least 80%, preferred at least 90%, more preferred at least 95% degree of sequence identity on the nucleic acid level to the DNA sequences encoding a stretch which is involved in the binding region defined in SEQ ID No.s 1-58 as well as fragments thereof encoding the biomarkers according to the present invention.

The before mentioned definitions for biomarker proteins and for genes encoding said biomarker proteins apply to every single embodiment of this inventions, any specific method, kit etc.

The determination of percent identity between two sequences is accomplished using the mathematical algorithm of Karlin and Altschul (1993) Proc. Natl. Acad. Sci. USA 90: 5873-5877. Such an algorithm is incorporated into the BLASTN and BLASTP programs of Altschul et al. (1990) J. Mol. Biol. 215: 403-410. BLAST nucleotide searches may be performed with the BLASTN program, score=100, word length=12, to obtain nucleotide sequences homologous to variant polypeptide encoding nucleic acids. BLAST protein searches are performed with the BLASTP program, score=50, wordlength=3, to obtain amino acid sequences homologous to the variant polypeptide, respectively. To obtain gapped alignments for comparative purposes, Gapped BLAST is utilized as described in Altschul et al. (1997) Nucleic Acids Res. 25: 3389-3402. When utilizing BLAST and Gapped BLAST programs, the default parameters of the respective programs are used.

The immunoglobulin(s) to be detected may be selected from IgA, IgD, IgG and IgM. In a preferred embodiment the immunoglobulin(s) to be detected is IgA or IgG. In the most preferred embodiment the immunoglobulin is IgA. The immunoglobulin(s) to be detected is not related to IgA rheumatoid factor.

In another preferred embodiment subsets of biomarker proteins may be used to assess the responsiveness to an anti-TNF treatment prior, during and/or after anti-TNFα treatment.

The respective set of proteins can not only predict responsiveness before, but also during treatment. Thus, a diagnostic assay based on one or more protein of the set will help the clinician in treatment decisions and the identification of anti-TNF therapy responders and non-responders a priory.

The bodily fluid and/or excrement from the individual to be assessed may be selected from a group comprising: blood, saliva, tears, synovial and spinal fluid, plasma, urine and stool.

An individual who is to be subjected to or is being subjected to an anti-TNFα treatment may suffer autoimmune conditions such as Crohn's disease, ulcerative colitis, psoriasis, psoriatic arthritis, ankylosing spondylitis, spondyloarthropathies, rheumatoid arthritis etc.

The method of the invention is especially suited for individuals suffering from rheumatoid arthritis.

Subject of the present invention is furthermore a kit for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment to assess the responsiveness to an anti-TNF treatment which comprises one or more biomarker proteins, wherein a biomarker protein is an expression product encoded by a gene selected from the group comprising RAB11B, PPP2R1A, KPNB1, COG4 and FDFT1. In a preferred embodiment the kit comprises at least those proteins encoded by a gene selected from the group comprising RAB11B, PPP2R1A, KPNB1, COG4 and FDFT1.

In a preferred embodiment of the inventive kit at least two of the biomarker proteins of the protein marker group are detected wherein a biomarker protein is an expression product encoded by a gene selected from the group comprising RAB11B, PPP2R1A, KPNB1, COG4 and FDFT1 (Protein Set 1=RAB11B, PPP2R1A, KPNB1, COG4 and FDFT1). In another preferred embodiment of the inventive kit at least one expression product encoded by genes RAB11B, PPP2R1A, KPNB1, COG4 and FDFT1 are detected. In another preferred embodiment only expression products encoded by genes RAB11B, PPP2R1A, KPNB1, COG4 and FDFT1 are detected. In another preferred embodiment each and only the expression products encoded by genes RAB11B, PPP2R1A, KPNB1, COG4 and FDFT1 are detected.

In another preferred embodiment of the kit for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment according to the invention the biomarker protein group additionally comprises at least one other expression product encoded by a gene selected from the group comprising PECI, CTNND2, NSMCE1, KTELC1, HS6ST1, ARMC6, TH1L, PSME1, GPC1, EDC4 (Protein Set 2) and at least one of the proteins of the entire group 1 and 2 (Protein Set 1 and 2) is detected. In a preferred embodiment of the invention at least one protein from Protein Set 1 is detected and additionally at least one of Protein Set 2 is detected. In another preferred embodiment at least two of the proteins of Protein Set 1 and additionally at least one of Protein Set 2 are detected. In another preferred embodiment Protein Set 1 and Protein Set 2 are detected.

In another preferred embodiment additionally to the above cited combinations of marker proteins a protein of Protein Set 3 is detected: the Protein Set 3 comprises the expression products encoded by genes PRC1, NAT6, EEF1AL3, NP_(—)612480.1, PLXNA2, ELMO2 and NDUFS2.

In another preferred embodiment of the kit the biomarker protein group additionally comprises at least one expression product encoded by genes PECI, CTNND2, NSMCE1, KTELC1, HS6ST1, ARMC6, TH1L, PSME1, GPC1, EDC4, PRC1, NAT6, EEF1AL3, NP_(—)612480.1, PLXNA2, ELMO2 and NDUFS2.

Another preferred embodiment of the invention is a kit for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment to assess the responsiveness to an anti-TNF treatment which comprises at least two biomarker proteins, wherein a biomarker protein is an expression product encoded by a gene selected from the group comprising RAB11B, PPP2R1A, KPNB1, COG4, FDFT1, PECI, CTNND2, NSMCE1, KTELC1, HS6ST1, ARMC6, TH1L, PSME1, GPC1, EDC4, PRC1, NAT6, EEF1AL3, NP_(—)612480.1, PLXNA2, ELMO2 and NDUFS2.

As outlined above subject of the present invention is a method, wherein markers are detected and used to identify non-responder. A further embodiment of the present invention is the provision of marker(s), wherein the detection of those marker(s) is indicative for responder.

Thus, subject of the present invention is further a method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment to assess the responsiveness to an anti-TNF treatment which comprises:

-   -   Detection of immunoglobulin(s) against one or more biomarker         proteins in a bodily fluid or excrement of said patient, wherein         a biomarker protein is an artificial peptides deduced from an         expression product in an incorrect reading frame of a gene         selected from the group comprising IRAK1 and C20orf149, wherein         an individual positive for at least one of said         immunoglobulin(s) is classified as responder.

In a preferred embodiment of the above-identified method the individual is sorted into one of two categories based on detection of said immunoglobulin(s), wherein an individual positive for at least one of said immunoglobulin(s) is classified as responder and, wherein an individual negative for any of said detected immunoglobulin(s) is classified as NON-responder.

In a preferred embodiment of the present invention the method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment the biomarker protein group additionally comprises at least one other expression product encoded by a gene selected from a group comprising PSCD2L and PPIA.

In another preferred embodiment all members of the biomarker group are detected, the group comprising either artificial peptides deduced from an expression product in an incorrect reading frame of a gene or the expression products encoded by the following genes IRAK1 and C20orf149 as well as PSCD2L and PPIA.

The immunoglobulin(s) to be detected may be selected from IgA, IgD, IgG and IgM. In a preferred embodiment the immunoglobulin(s) to be detected is IgA or IgG. In the most preferred embodiment the immunoglobulin is IgG. The immunoglobulin(s) to be detected is not related to IgA rheumatoid factor.

Subject of the method of the present invention is a method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment, wherein the immunoglobulin(s) is IgA and/or IgG. IgG is especially preferred in the context of a method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment to assess the responsiveness to an anti-TNF treatment, wherein an individual positive for at least one of before said immunoglobulin(s) is classified as responder.

The respective set of proteins can not only predict responsiveness before, but also during treatment. Thus, a diagnostic assay based on one or more protein of the set will help the clinician in treatment decisions and the identification of anti-TNF therapy responders and non-responders a priory.

The bodily fluid and/or excrement from the individual to be assessed may be selected from a group comprising: blood, saliva, tears, synovial and spinal fluid, plasma, urine and stool.

An individual who is to be subjected to or is being subjected to an anti-TNFα treatment may suffer autoimmune conditions such as Crohn's disease, ulcerative colitis, psoriasis, psoriatic arthritis, ankylosing spondylitis, spondyloarthropathies, rheumatoid arthritis etc.

The method of the invention is especially suited for individuals suffering from rheumatoid arthritis.

Subject of the present invention is also a kit for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment to assess the responsiveness to an anti-TNF treatment which comprises one or more biomarker proteins, wherein a biomarker protein is an artificial peptides deduced from an expression product in an incorrect reading frame of a gene selected from the group comprising IRAK1 and C20orf149.

In a preferred embodiment of the present invention the kit for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment the biomarker protein group additionally comprises at least one other expression product encoded by a gene selected from a group comprising PSCD2L and PPIA.

In another preferred embodiment all members of the biomarker group are detected, the group to comprising either artificial peptides deduced from an expression product in an incorrect reading frame of a gene or the expression products encoded by the following genes IRAK1 and C20orf149 as well as PSCD2L and PPIA.

In another embodiment of the invention the kit and the method according to the present invention is may additionally comprise one or more known diagnostic markers e.g. for autoimmune disorders. In a preferred embodiment the kit may also comprise other known diagnostic markers for rheumatoid arthritis.

The proteins, protein sets/kits may be conducted in different assay types known to a person skilled in the art.

The immunoglobulins to be detected are in or isolated from body fluids and excrements, such as blood, saliva, tears, synovial and spinal fluid, plasma, urine and stool, etc.

The diagnostic assay can be of any type applied in the field of diagnostics, including but not restricted to assays methods based on

-   -   enzymatic reactions     -   luminescence     -   fluorescence     -   radiochemicals

The preferred detection methods comprise strip tests, radioimmunoassay, chemiluminescence- and fluorescence-immunoassay, Immunoblot assay, Enzyme-linked immunoassay (ELISA), Luminex-based bead arrays, and protein microarray assay.

The assay types can further be microlitre plate-based, chip-based, bead-based, wherein the biomarker proteins can be attached to the surface or in solution.

The assays can be homogenous or heterogeneous assays, sandwich assays, competitive and non-competitive assays (The Immunoassay Handbook, Ed. David Wild, Elsevier LTD, Oxford; 3rd ed. (May 2005), ISBN-13: 978-0080445267; Hultschig C et al., Curr Opin Chem Biol. 2006 February; 10(1):4-10. PMID: 16376134).

TNFα treatment is conducted by administration of a TNF inhibitor to an individual in need thereof. TNF inhibitors are biologicals which bind to soluble and cell membrane-associated form of TNFα and neutralise the proinflammatory effect of TNF by preventing the binding of TNFα to the TNF-RI/II cell-surface receptors. The TNF inhibitors can be anti-TNFα antibodies or receptor molecules but also of other types. The essential of a TNF inhibitor according to the present invention is the ability to capture TNF before it binds to the TNF receptor on the cells.

Subject to the present invention is also the use of the biomarker proteins and/or protein sets and the kits comprising these biomarker proteins and/or protein sets according to the present invention for assessing the responsiveness to an anti-TNFα treatment of an individual who is to be subjected to or is being subjected to an anti-TNFα treatment.

FIGURE DESCRIPTION

FIG. 1 shows SEQ ID No. 1 which is a DNA sequence of the gene RAB11B (Table 1, No. 1)

FIG. 2 shows SEQ ID No. 2 which is a DNA sequence of the gene PPP2R1A (Table 1, No. 2)

FIG. 3 shows SEQ ID No. 3 which is a DNA sequence of the gene PPP2R1A (Table 1, No. 2)

FIG. 4 shows SEQ ID No. 4 which is a DNA sequence of the gene KPNB1 (Table 1, No. 3)

FIG. 5 shows SEQ ID No. 5 which is a DNA sequence of the gene COG4 (Table 1, No. 4)

FIG. 6 shows SEQ ID No. 6 which is a DNA sequence of the gene COG4 (Table 1, No. 4)

FIG. 7 shows SEQ ID No. 7 which is a DNA sequence of the gene COG4 (Table 1, No. 4)

FIG. 8 shows SEQ ID No. 8 which is a DNA sequence of the gene COG4 (Table 1, No. 4)

FIG. 9 shows SEQ ID No. 9 which is a DNA sequence of the gene FDFT1 (Table 1, No. 5)

FIG. 10 shows SEQ ID No. 10 which is a DNA sequence of the gene PECI (Table 1, No. 6)

FIG. 11 shows SEQ ID No. 11 which is a DNA sequence of the gene PECI (Table 1, No. 6)

FIG. 12 shows SEQ ID No. 12 which is a DNA sequence of the gene PECI (Table 1, No. 6)

FIG. 13 shows SEQ ID No. 13 which is a DNA sequence of the gene PECI (Table 1, No. 6)

FIG. 14 shows SEQ ID No. 14 which is a DNA sequence of the gene PECI (Table 1, No. 6)

FIG. 15 shows SEQ ID No. 15 which is a DNA sequence of the gene CTNND2 (Table 1, No. 7)

FIG. 16 shows SEQ ID No. 16 which is a DNA sequence of the gene CTNND2 (Table 1, No. 7)

FIG. 17 shows SEQ ID No. 17 which is a DNA sequence of the gene NSMCE1 (Table 1, No. 8)

FIG. 18 shows SEQ ID No. 18 which is a DNA sequence of the gene NSMCE1 (Table 1, No. 8)

FIG. 19 shows SEQ ID No. 19 which is a DNA sequence of the gene NSMCE1 (Table 1, No. 8)

FIG. 20 shows SEQ ID No. 20 which is a DNA sequence of the gene KTELC1 (Table 1, No. 9)

FIG. 21 shows SEQ ID No. 21 which is a DNA sequence of the gene HS6ST1 (Table 1, No. 10)

FIG. 22 shows SEQ ID No. 22 which is a DNA sequence of the gene ARMC6 (Table 1, No. 11)

FIG. 23 shows SEQ ID No. 23 which is a DNA sequence of the gene ARMC6 (Table 1, No. 11)

FIG. 24 shows SEQ ID No. 24 which is a DNA sequence of the gene ARMC6 (Table 1, No. 11)

FIG. 25 shows SEQ ID No. 25 which is a DNA sequence of the gene ARMC6 (Table 1, No. 11)

FIG. 26 shows SEQ ID No. 26 which is a DNA sequence of the gene TH1L (Table 1, No. 12)

FIG. 27 shows SEQ ID No. 27 which is a DNA sequence of the gene PSME1 (Table 1, No. 13)

FIG. 28 shows SEQ ID No. 28 which is a DNA sequence of the gene PSME1 (Table 1, No. 13)

FIG. 29 shows SEQ ID No. 29 which is a DNA sequence of the gene GPC1 (Table 1, No. 14)

FIG. 30 shows SEQ ID No. 30 which is a DNA sequence of the gene EDC4 (Table 1, No. 15)

FIG. 31 shows SEQ ID No. 31 which is a DNA sequence of the gene EDC4 (Table 1, No. 15)

FIG. 32 shows SEQ ID No. 32 which is a DNA sequence of the gene PRC1 (Table 1, No. 16)

FIG. 33 shows SEQ ID No. 33 which is a DNA sequence of the gene PRC1 (Table 1, No. 16)

FIG. 34 shows SEQ ID No. 34 which is a DNA sequence of the gene PRC1 (Table 1, No. 16)

FIG. 35 shows SEQ ID No. 35 which is a DNA sequence of the gene NAT6 (Table 1, No. 17)

FIG. 36 shows SEQ ID No. 36 which is a DNA sequence of the gene NAT6 (Table 1, No. 17)

FIG. 37 shows SEQ ID No. 37 which is a DNA sequence of the gene NAT6 (Table 1, No. 17)

FIG. 38 shows SEQ ID No. 38 which is a DNA sequence of the gene EEF1AL3 (Table 1, No. 18)

FIG. 39 shows SEQ ID No. 39 which is a DNA sequence of the gene NP_(—)612480.1 (Table 1, No. 19)

FIG. 40 shows SEQ ID No. 40 which is a DNA sequence of the gene PLXNA2 (Table 1, No. 20)

FIG. 41 shows SEQ ID No. 41 which is a DNA sequence of the gene PLXNA2 (Table 1, No. 20)

FIG. 42 shows SEQ ID No. 42 which is a DNA sequence of the gene ELMO2 (Table 1, No. 21)

FIG. 43 shows SEQ ID No. 43 which is a DNA sequence of the gene ELMO2 (Table 1, No. 21)

FIG. 44 shows SEQ ID No. 44 which is a DNA sequence of the gene ELMO2 (Table 1, No. 21)

FIG. 45 shows SEQ ID No. 45 which is a DNA sequence of the gene ELMO2 (Table 1, No. 21)

FIG. 46 shows SEQ ID No. 46 which is a DNA sequence of the gene NDUFS2 (Table 1, No. 22)

FIG. 47 shows SEQ ID No. 47 which is a DNA sequence of the gene NDUFS2 (Table 1, No. 22)

FIG. 48 shows SEQ ID No. 48 which is a DNA sequence of the gene IRAK1 (Table 1, No. 23)

FIG. 49 shows SEQ ID No. 49 which is a DNA sequence of the gene IRAK1 (Table 1, No. 23)

FIG. 50 shows SEQ ID No. 50 which is a DNA sequence of the gene IRAK1 (Table 1, No. 23)

FIG. 51 shows SEQ ID No. 51 which is a DNA sequence of the gene IRAK1 (Table 1, No. 23)

FIG. 52 shows SEQ ID No. 52 which is a DNA sequence of the gene IRAK1 (Table 1, No. 23)

FIG. 53 shows SEQ ID No. 53 which is a DNA sequence of the gene C20orf149 (Table 1, No. 24)

FIG. 54 shows SEQ ID No. 54 which is a DNA sequence of the gene C20orf149 (Table 1, No. 24)

FIG. 55 shows SEQ ID No. 55 which is a DNA sequence of the gene C20orf149 (Table 1, No. 24)

FIG. 56 shows SEQ ID No. 56 which is a DNA sequence of the gene PCSD2L (Table 1, No. 25)

FIG. 57 shows SEQ ID No. 57 which is a DNA sequence of the gene PCSD2L (Table 1, No. 25)

FIG. 58 shows SEQ ID No. 58 which is a DNA sequence of the gene PPIA (Table 1, No. 26)

FIG. 59 shows SEQ ID No. 59 which is a Protein sequence of the gene RAB11B (Table 1, No. 1)

FIG. 60 shows SEQ ID No. 60 which is a Protein sequence of the gene PPP2R1A (Table 1, No. 2)

FIG. 61 shows SEQ ID No. 61 which is a Protein sequence of the gene PPP2R1A (Table 1, No. 2)

FIG. 62 shows SEQ ID No. 62 which is a Protein sequence of the gene KPNB1 (Table 1, No. 3)

FIG. 64 shows SEQ ID No. 64 which is a Protein sequence of the gene COG4 (Table 1, No. 4)

FIG. 65 shows SEQ ID No. 65 which is a Protein sequence of the gene COG4 (Table 1, No. 4)

FIG. 66 shows SEQ ID No. 66 which is a Protein sequence of the gene COG4 (Table 1, No. 4)

FIG. 67 shows SEQ ID No. 67 which is a Protein sequence of the gene COG4 (Table 1, No. 4)

FIG. 68 shows SEQ ID No. 68 which is a Protein sequence of the gene FDFT1 (Table 1, No. 5)

FIG. 69 shows SEQ ID No. 69 which is a Protein sequence of the gene PECI (Table 1, No. 6)

FIG. 70 shows SEQ ID No. 70 which is a Protein sequence of the gene PECI (Table 1, No. 6)

FIG. 71 shows SEQ ID No. 71 which is a Protein sequence of the gene PECI (Table 1, No. 6)

FIG. 72 shows SEQ ID No. 72 which is a Protein sequence of the gene PECI (Table 1, No. 6)

FIG. 73 shows SEQ ID No. 73 which is a Protein sequence of the gene PECI (Table 1, No. 6)

FIG. 74 shows SEQ ID No. 74 which is a Protein sequence of the gene CTNND2 (Table 1, No. 7)

FIG. 75 shows SEQ ID No. 75 which is a Protein sequence of the gene CTNND2 (Table 1, No. 7)

FIG. 76 shows SEQ ID No. 76 which is a Protein sequence of the gene NSMCE1 (Table 1, No. 8)

FIG. 77 shows SEQ ID No. 77 which is a Protein sequence of the gene NSMCE1 (Table 1, No. 8)

FIG. 78 shows SEQ ID No. 78 which is a Protein sequence of the gene NSMCE1 (Table 1, No. 8)

FIG. 79 shows SEQ ID No. 79 which is a Protein sequence of the gene KTELC1 (Table 1, No. 9)

FIG. 80 shows SEQ ID No. 80 which is a Protein sequence of the gene HS6ST1 (Table 1, No. 10)

FIG. 81 shows SEQ ID No. 81 which is a Protein sequence of the gene ARMC6 (Table 1, No. 11)

FIG. 82 shows SEQ ID No. 82 which is a Protein sequence of the gene ARMC6 (Table 1, No. 11)

FIG. 83 shows SEQ ID No. 83 which is a Protein sequence of the gene ARMC6 (Table 1, No. 11)

FIG. 84 shows SEQ ID No. 84 which is a Protein sequence of the gene ARMC6 (Table 1, No. 11)

FIG. 85 shows SEQ ID No. 85 which is a Protein sequence of the gene TH1L (Table 1, No. 12)

FIG. 86 shows SEQ ID No. 86 which is a Protein sequence of the gene PSME1 (Table 1, No. 13)

FIG. 87 shows SEQ ID No. 87 which is a Protein sequence of the gene PSME1 (Table 1, No. 13)

FIG. 88 shows SEQ ID No. 88 which is a Protein sequence of the gene GPC1 (Table 1, No. 14)

FIG. 89 shows SEQ ID No. 89 which is a Protein sequence of the gene EDC4 (Table 1, No. 15)

FIG. 90 shows SEQ ID No. 90 which is a Protein sequence of the gene EDC4 (Table 1, No. 15)

FIG. 91 shows SEQ ID No. 91 which is a Protein sequence of the gene PRC1 (Table 1, No. 16)

FIG. 92 shows SEQ ID No. 92 which is a Protein sequence of the gene PRC1 (Table 1, No. 16)

FIG. 93 shows SEQ ID No. 93 which is a Protein sequence of the gene PRC1 (Table 1, No. 16)

FIG. 94 shows SEQ ID No. 94 which is a Protein sequence of the gene NAT6 (Table 1, No. 17)

FIG. 95 shows SEQ ID No. 95 which is a Protein sequence of the gene NAT6 (Table 1, No. 17)

FIG. 96 shows SEQ ID No. 96 which is a Protein sequence of the gene NAT6 (Table 1, No. 17)

FIG. 97 shows SEQ ID No. 97 which is a Protein sequence of the gene EEF1AL3 (Table 1, No. 18)

FIG. 98 shows SEQ ID No. 98 which is a Protein sequence of the gene NP_(—)612480.1 (Table 1, No. 19)

FIG. 99 shows SEQ ID No. 99 which is a Protein sequence of the gene PLXNA2 (Table 1, No. 20)

FIG. 100 shows SEQ ID No. 100 which is a Protein sequence of the gene PLXNA2 (Table 1, No. 20)

FIG. 101 shows SEQ ID No. 101 which is a Protein sequence of the gene ELMO2 (Table 1, No. 21)

FIG. 102 shows SEQ ID No. 102 which is a Protein sequence of the gene ELMO2 (Table 1, No. 21)

FIG. 103 shows SEQ ID No. 103 which is a Protein sequence of the gene ELMO2 (Table 1, No. 21)

FIG. 104 shows SEQ ID No. 104 which is a Protein sequence of the gene ELMO2 (Table 1, No. 21)

FIG. 105 shows SEQ ID No. 105 which is a Protein sequence of the gene NDUFS2 (Table 1, No. 22)

FIG. 106 shows SEQ ID No. 106 which is a Protein sequence of the gene NDUFS2 (Table 1, No. 22)

FIG. 107 shows SEQ ID No. 107 which is a Protein sequence of the gene IRAK1 (Table 1, No. 23)

FIG. 108 shows SEQ ID No. 108 which is a Protein sequence of the gene IRAK1 (Table 1, No. 23)

FIG. 109 shows SEQ ID No. 109 which is a Protein sequence of the gene IRAK1 (Table 1, No. 23)

FIG. 110 shows SEQ ID No. 110 which is a Protein sequence of the gene IRAK1 (Table 1, No. 23)

FIG. 111 shows SEQ ID No. 111 which is a Protein sequence of the gene IRAK1 (Table 1, No. 23)

FIG. 112 shows SEQ ID No. 112 which is a Protein sequence of the gene C20orf149 (Table 1, No. 24)

FIG. 113 shows SEQ ID No. 113 which is a Protein sequence of the gene C20orf149 (Table 1, No. 24)

FIG. 114 shows SEQ ID No. 114 which is a Protein sequence of the gene C20orf149 (Table 1, No. 24)

FIG. 115 shows SEQ ID No. 115 which is a Protein sequence of the gene PCSD2L (Table 1, No. 25)

FIG. 116 shows SEQ ID No. 116 which is a Protein sequence of the gene PCSD2L (Table 1, No. 25)

FIG. 117 shows SEQ ID No. 117 which is a Protein sequence of the gene PPIA (Table 1, No. 26)

FIG. 118 shows SEQ ID No. 118 which is a Protein sequence derived from an incorrect reading frame of the gene HS6ST1 (Table 1, No. 10)

FIG. 119 shows SEQ ID No. 119 which is a Protein sequence derived from an incorrect reading frame of the gene IRAK1 (Table 1, No. 23)

FIG. 120 shows SEQ ID No. 120 which is a Protein sequence derived from an incorrect reading frame of the gene C20orf149 (Table 1, No. 24)

FIG. 121 shows SEQ ID No. 121 which is a Protein sequence derived from an incorrect reading frame of the gene C20orf149 (Table 1, No. 24)

FIG. 122 shows SEQ ID No. 122 which is a Protein sequence derived from an incorrect reading frame of the gene HS6SP1 (Table 1, No. 10)

EXAMPLES

The set of proteins which are subject of the present invention have been found by conducting serum screening experiments on protein macroarrays. The protein macroarrays consist of >38.000 individual E. coli clones expressing human gene fragments cloned from a foetal brain cDNA library. These fragments can be full length proteins and fragments thereof, as well as artificial peptides resulting from translation products in the incorrect reading frame. The technology for screening was developed at the MPI for Molecular Genetics and constitutes prior art; Büssow K, et al. Nucleic Acids Res. 1998 Nov. 1; 26(20:5007-8. PMID: 9776767; Büssow K, et al. Genomics 2000 Apr. 1; 65(1):1-8. PMID: 10777659) and has been applied since then in multiple scientific publications (e.g. Horn S, et al. Proteomics. 2006 January; 6(2):605-13. PMID: 16419013; Lueking A, et al. Mol Cell Proteomics. 2005 September; 4(9):1382-90. PMID: 15939964). The only amendment to the method described in the original paper is the incubation with patient serum and the use of specific secondary antibodies directed against different immunoglobulin isotypes such as IgG, IgA, IgM and IgD as described beneath:

Patient serum was diluted 1:40 in blocking buffer (3% Milk powder/TBST) and incubated overnight at room temperature, kept in slow motion on an orbital shaker. After incubation filters are washed 3×20 min. in TBST, followed by a second incubation for 1 h at room temperature with anti human IgG or anti human IgA secondary antibody (mouse) conjugated with alkaline phosphatase, 1:1000 in blocking buffer. Positive signals on the macroarray (PVDF filter) were recorded as described and correlated to the original E. coli clones stored in 384-well microtitre plates. E. coli clones corresponding with the signals on the macroarray were sequenced to obtain information of the insert, and hence the gene fragment of which the translation product is recognised by the patient sera. These fragments can be full length proteins and fragments thereof, as well as artificial peptides resulting from out-of frame-translation products.

The protein macroarrays were screened with pools of anti-TNFα treatment (Adalimumab®; Humira) responder and non-responder patient sera before and after therapy. Responder and non-responder patients were categorised according to the clinical response evaluated after 1 year (or at drop-out) in accordance with the European League Against Rheumatism criteria using the modified disease activity score that includes 28 joints (DAS 28). The DAS28 score and the European League Against Rheumatism (EULAR) response criteria are widely used to record disease activity and therapeutic response in patients with RA (Van Gestel A M et al. Arthritis Rheum 1996; 39:34-40. PMID:

The DAS28 was developed and validated for patients with RA, and in addition to disease activity it also reflects the patient's satisfaction with reasonable accuracy. This composite index comprises 4 items, namely, swollen joint count (SJC), tender joint count (TJC), a visual analog scale (VAS) of the patient's assessment of general health (GH), and erythrocyte sedimentation rate (ESR; first hour), which are also part of the American College of Rheumatology (ACR) response criteria.

Description of the Used Patient Sera:

DAS28 values from 2 RA patient cohorts comprising 3 patients each were compared and sera of these patients before and after therapy were used for screening the protein macroarrays. RA cohort 1 (RA1) consisted of therapy responder patients and the RA cohort 2 (RA2) consisted of of age- and sex-matched patients seen during the same period who were therapy non-responders. Item weighting, factor loading, and internal consistency were assessed by factor analysis, principal component analysis, and calculation of Cronbach's alpha. The range of DAS 28 scores in the responder group initially before treatment was from 4.4-6 with a mean value of 4.83 and in the non responder group 4.1-8.6 with a mean value 6.2. Responder had a mean change of 2.36 during therapy while there was no mean change in the DAS28 in the non responder group.

Table 1 (consisting of Table 1 A and Table 1 B) shows a summary list of genes of which the expression products represent biomarker proteins and artificial peptides resulting from translation products in the incorrect reading frame found to be predictive for responsiveness to anti-TNFα antibody treatment (Adalimumab; Humira) of the patient groups described above having been subjected to an anti-TNFα treatment.

TABLE 1 A List of candidate genes encoding a biomarker set detected by immunoglobulins of TNF inhibitor therapy NON-RESPONDER patients frame ENSEMBL HGNC No. Importance offset gene identifier gene symbol gene description and alternative identifiers 1 1: High 0 ENSG00000185236 RAB11B Ras-related protein Rab-11B (GTP-binding protein YPT3). [Source: Uniprot/SWISSPROT; Acc: Q15907] 2 1: High 0 ENSG00000105568 PPP2R1A Serine/threonine-protein phosphatase 2A 65 kDa regulatory subunit A alpha isoform (PP2A, subunit A, PR65-alpha isoform) (PP2A, subunit A, R1-alpha isoform) (Medium tumor antigen-associated 61 kDa protein). [Source: Uniprot/SWISSPROT; Acc: P30153] 3 1: High 0 ENSG00000108424 KPNB1 Importin beta-1 subunit (Karyopherin beta-1 subunit) (Nuclear factor P97) (Importin 90). [Source: Uniprot/SWISSPROT; Acc: Q14974] 4 1: High 0 ENSG00000103051 COG4 Conserved oligomeric Golgi complex component 4. [Source: Uniprot/SWISSPROT; Acc: Q9H9E3] 5 1: High 0 ENSG00000079459 FDFT1 Squalene synthetase (EC 2.5.1.21) (SQS) (SS) (Farnesyl-diphosphate farnesyltransferase) (FPP:FPP farnesyltransferase). [Source: Uniprot/SWISSPROT; Acc: P37268] 6 2: Medium 0 ENSG00000198721 PECI Peroxisomal 3,2-trans-enoyl-CoA isomerase (EC 5.3.3.8) (Dodecenoyl-CoA isomerase) (Delta(3),delta(2)-enoyl-CoA isomerase) (D3,D2-enoyl-CoA isomerase) (DBI-related protein 1) (DRS-1) (Hepatocellular carcinoma-associated antigen 88) (Renal carcinoma antige 7 2: Medium 0 ENSG00000169862 CTNND2 Catenin delta-2 (Delta-catenin) (Neural plakophilin-related ARM-repeat protein) (NPRAP) (Neurojungin) (GT24). [Source: Uniprot/SWISSPROT; Acc: Q9UQB3] chromosome NCBI36:5:11024952-11957110:-1 8 2: Medium 0 ENSG00000169189 NSMCE1 non-SMC element 1 homolog [Source: RefSeq_peptide; Acc: NP_659547] chromosome_NCBI36:16:27143817-27187586:-1 9 2: Medium 0 ENSG00000163389 KTELC1 KTEL motif-containing protein 1 precursor (CAP10-like 46 kDa protein) (Myelodysplastic syndromes relative protein). [Source: Uniprot/SWISSPROT; Acc: Q8NBL1] 10 2: Medium −1 ENSG00000136720 HS6ST1 Heparan-sulfate 6-O-sulfotransferase 1 (EC 2.8.2.—) (HS6ST-1). [Source: Uniprot/SWISSPROT; Acc: O60243] 11 2: Medium 0 ENSG00000105676 ARMC6 Armadillo repeat-containing protein 6. [Source: Uniprot/SWISSPROT; Acc: Q6NXE6]chromosome_NCBI36:19:19005538-19029985:1 12 2: Medium 0 ENSG00000101158 TH1L Negative elongation factor C/D (NELF-C/D) (TH1-like protein). [Source: Uniprot/SWISSPROT; Acc: Q8IXH7] 13 2: Medium 0 ENSG00000092010 PSME1 Proteasome activator complex subunit 1 (Proteasome activator 28-alpha subunit) (PA28alpha) (PA28a) (Activator of multicatalytic protease subunit 1) (11S regulator complex subunit alpha) (REG-alpha) (Interferon gamma up-regulated I-5111 protein) (IGUP I-51 14 2: Medium 0 ENSG00000063660 GPC1 Glypican-1 precursor. [Source: Uniprot/SWISSPROT; Acc: P35052] 15 2: Medium 0 ENSG00000038358 EDC4 autoantigen RCD8 [Source: RefSeq_peptide; Acc: NP_055144] chromosome_NCBI36:16:66464500-66475906:1 16 3: Low 0 ENSG00000198901 PRC1 Protein regulator of cytokinesis 1. [Source: Uniprot/SWISSPROT; Acc: O43663] chromosome_NCBI36:15:89310279-89338808:-1 17 3: Low 0 ENSG00000186792 NAT6 Hyaluronidase-3 precursor (EC 3.2.1.35) (Hyal-3) (Hyaluronoglucosaminidase-3) (LUCA-3). [Source: Uniprot/SWISSPROT; Acc: O43820] chromosome_NCBI36:3:50300178-50311903:-1 18 3: Low 0 ENSG00000185637 EEF1AL3 Eukaryotic translation elongation factor 1 alpha 1 (Fragment). [Source: Uniprot/SPTREMBL; Acc: Q5JR01] chromosome_NCBI36:9:134884631- 134886374:1 19 3: Low 0 ENSG00000168005 NP_612480.1 chromosome_NCBI36:11:63337436-63351727:1 20 3: Low 0 ENSG00000076356 PLXNA2 Plexin-A2 precursor (Semaphorin receptor OCT). [Source: Uniprot/SWISSPROT; Acc: O75051] chromosome_NCBI36:1:206262210-206484288:-1 21 3: Low 0 ENSG00000062598 ELMO2 Engulfment and cell motility protein 2 (CED-12 homolog A) (hCED-12A). [Source: Uniprot/SWISSPROT; Acc: Q96JJ3] chromosome_NCBI36:20:44428096- 44468678:-1 22 3: Low 0 ENSG00000158864 NDUFS2 NADH-ubiquinone oxidoreductase 49 kDa subunit, mitochondrial precursor (EC 1.6.5.3) (EC 1.6.99.3) (Complex I-49 KD) (CI-49 KD). [Source: Uniprot/ SWISSPROT; Acc: O75306]

TABLE 1 B List of candidate genes encoding a biomarker set detected by immunoglobulins of TNF inhibitor therapy RESPONDER patients HGNC frame ENSEMBL gene No. Importance offset identifier symbol gene description and alternative identifiers 23 1: High −1 ENSG00000184216 IRAK1 Interleukin-1 receptor-associated kinase 1 (EC 2.7.11.1) (IRAK-1). [Source: Uniprot/SWISSPROT; Acc: P51617] 24 1: High −1 ENSG00000125534 C20orf149 UPF0362 protein C20orf149. [Source: Uniprot/SWISSPROT; Acc: Q9H3Y8] 25 2: Medium 0 ENSG00000105443 PSCD2L Cytohesin-2 (ARF nucleotide-binding site opener) (ARNO protein) (ARF exchange factor). [Source: Uniprot/SWISSPROT; Acc: Q99418] chromosome_NCBI36:19:53664424-53674457:1 26 3: Low 0 ENSG00000198618 PPIA Peptidyl-prolyl cis-trans isomerase A (EC 5.2.1.8) (PPlase A) (Rotamase A) (Cyclophilin A) (Cyclosporin A-binding protein). [Source: Uniprot/SWISSPROT; Acc: P62937] chromosome_NCBI36:21:19151917-19152651:1 

1. A method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment to assess the responsiveness to an anti-TNF treatment prior to anti-TNFα treatment which comprises: (a) Detection of immunoglobulin(s) against one or more biomarker proteins in a bodily fluid or an excrement of said patient, wherein the one or more biomarker is indicative for the responsiveness to an anti-TNF treatment prior to anti-TNFα treatment, (b) Sorting the individual into responder or NON-responder based on detection of said o immunoglobulin(s).
 2. A method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment to assess the responsiveness to an anti-TNF treatment prior, during and/or after anti-TNFα treatment which comprises: (c) Detection of immunoglobulin(s) against at least two biomarker proteins in a bodily fluid or an excrement of said patient, wherein the at least two biomarker are indicative for the responsiveness to an anti-TNF treatment prior to anti-TNFα treatment, (d) Sorting the individual into responder or NON-responder based on detection of said immunoglobulin(s). wherein the at least two biomarker proteins are selected from the group comprising RAB11B, PPP2R1A, KPNB1, COG4, FDFT1, PECI, CTNND2, NSMCE1, KTELC1, HS6ST1, ARMC6, TH1L, PSME1, GPC1, EDC4, PRC1, NAT6, EEF1AL3, NP_(—)612480.1, PLXNA2, ELMO2 and NDUFS2.
 3. A method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment to assess the responsiveness to an anti-TNF treatment which comprises: Detection of immunoglobulin(s) against one or more biomarker proteins in a bodily fluid or an excrement of said patient, wherein a biomarker protein is an expression product encoded by a gene selected from the group comprising RAB11B, PPP2R1A, KPNB1, COG4 and FDFT1, wherein an individual positive for at least one of said immunoglobulin(s) is classified as NON-Responder.
 4. A method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment according to claim 1, wherein the biomarker protein group additionally comprises at least one other expression product encoded by a gene selected from the group comprising PEC1, CTNND2, NSMCE1, KTELC1, HS6ST1, ARMC6, TH1L, PSME1, GPC1, EDC4, PRC1, NAT6, EEF1AL3, NP_(—)612480.1, PLXNA2, ELMO2 and NDUFS2.
 5. A method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment according to claim 1, wherein the immunoglobulin(s) is IgA and/or IgG.
 6. A method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment according to claim 1, wherein the bodily fluid and/or excrement may be selected from a group comprising: blood, saliva, tears, synovial and spinal fluid, plasma, urine and stool.
 7. A method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment according to claim 1, wherein the individual suffers from rheumatoid arthritis.
 8. A kit for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment to assess the responsiveness to an anti-TNF treatment which comprises one or more biomarker proteins, wherein a biomarker protein is an expression product encoded by a gene selected from the group comprising RAB11B, PPP2R1A, KPNB1, COG4 and FDFT1.
 9. A kit according to claim 8 wherein the biomarker protein group additionally comprises at least one other expression product encoded by a gene selected from the group comprising PEC1, CTNND2, NSMCE1, KTELC1, HS6ST1, ARMC6, TH1L, PSME1, GPC1, EDC4, PRC1, NAT6, EEF1 AL3, NP_(—)612480.1, PLXNA2, ELMO2 and NDUFS2.
 10. A kit for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment to assess the responsiveness to an anti-TNF treatment which comprises at least two biomarker proteins, wherein a biomarker protein is an expression product encoded by a gene selected from the group comprising RAB11B, PPP2R1A, KPNB1, COG4, FDFT1, PEC1, CTNND2, NSMCE1, KTELC1, HS6ST1, ARMC6, TH1L, PSME1, GPC1, EDC4, PRC1, NAT6, EEF1 AL3, NPJS12480.1, PLXNA2, ELMO2 and NDUFS2.
 11. A method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment to assess the responsiveness to an anti-TNF treatment which comprises; Detection of immunoglobulin(s) against one or more biomarker proteins in a bodily fluid or an excrement of said patient, wherein a biomarker protein is an artificial peptide deduced from an expression product in an incorrect reading frame of a gene selected from the group comprising IRAKI and C20orf149, wherein an individual positive for at least one of said immunoglobulin(s) is classified as responder.
 12. A method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment according to claim 11, wherein the biomarker protein group additionally comprises at least one other expression product encoded by a gene selected from the group comprising PSCD2L and PPIA.
 13. A method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment according to claim 11, wherein the immunoglobulin(s) is IgA and/or IgG.
 14. A method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment according to claim 11, wherein the bodily fluid and/or excrement may be selected from a group comprising: blood, saliva, tears, synovial and spinal fluid, plasma, urine and stool.
 15. A method for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment according to claim 11, wherein the individual suffers from rheumatoid arthritis.
 16. A kit for diagnosing an individual who is to be subjected to or is being subjected to an anti-TNFα treatment to assess the responsiveness to an anti-TNF treatment which comprises one or more biomarker proteins, wherein a biomarker protein is an artificial peptide deduced from an expression product in an incorrect reading frame of a gene selected from the group comprising IRAKI and C20orf149.
 17. A kit according to claim 8, wherein the biomarker protein group additionally comprises at least one other expression product encoded by a gene selected from the group comprising PSCD2L and PPIA.
 18. The use of a kit according to claim 8 for assessing the responsiveness to an anti-TNFα treatment of an individual who is to be subjected to or is being subjected to an anti-TNFα treatment. 